AI Product Manager

JOB SUMMARY
This role requires working onsite 4 days per week.

Key Responsibilities
Define product vision, strategy, roadmap, and success metrics for AI and GenAI products across business and enterprise functions.
Identify and prioritize use cases based on value, feasibility, data readiness, risk profile, platform readiness, AWS/cloud dependencies, user impact, and strategic alignment.
Translate business needs into product requirements, user stories, acceptance criteria, operating requirements, governance requirements, and measurable outcomes.
Manage product lifecycle from discovery, experimentation, MVP, pilot, production rollout, adoption, monitoring, and continuous improvement.
Partner with AI engineers, researchers, cloud/platform teams, architects, UX, risk, compliance, legal, cybersecurity, data owners, and business stakeholders.
Define KPIs such as adoption, productivity gain, cost reduction, cycle-time reduction, accuracy, risk reduction, user satisfaction, operational efficiency, and control effectiveness.
Ensure AI products include appropriate governance, human oversight, explainability, auditability, security, data privacy, and Responsible AI controls.
Drive AI-native adoption through change management, training, communication, feedback loops, executive reporting, and responsible citizen-development enablement.

Required Qualifications
Experience in product management, digital transformation, AI/ML products, data platforms, enterprise technology, or business transformation.
Strong understanding of AI, GenAI, LLM capabilities, limitations, risks, and enterprise adoption considerations.
Ability to translate business problems into AI-enabled product opportunities, roadmaps, requirements, and measurable outcomes.
Experience working with engineering, data science, research, architecture, risk, compliance, cybersecurity, legal, and business stakeholders.
Strong roadmap management, prioritization, stakeholder engagement, business-case development, delivery governance, and adoption-management skills.
Working knowledge of AI platform dependencies, including cloud delivery, data readiness, governance approvals, security reviews, and production support.

Preferred Qualifications
Banking, financial services, fintech, risk, operations, compliance, customer service, banker productivity, or enterprise productivity background.
Experience delivering AI copilots, knowledge assistants, automation tools, analytics products, AI platforms, data products, or citizen-development programs.
Familiarity with AIRP-style platform models, AWS-hosted AI platforms, Power Platform, Copilot Studio, Power Apps, Power Automate, Power BI, AI governance, model risk, data privacy, cybersecurity, and Responsible AI requirements.